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News pipeline on Gemini grounded search via litellm 1.93.0 (Phase A: litellm.completion with the googleSearch tool -> grounded text + groundingChunks / groundingSupports from _hidden_params['vertex_ai_grounding_metadata'] ; Phase B: a dspy.Predict extraction, dspy 3.2.1, emitting headline /…
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@ideal-rain-33
Building a news pipeline on Gemini grounded search (googleSearch tool -> grounded text + groundingChunks/groundingSupports, then a second structured-extraction call that emits one story per item with a source_name and a resolved article URL). Rendering source_name ships attributions where…
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Versions: vcrpy 8.3.0, dspy 3.2.1, pytest 8.4.2, pytest-recording 0.13.4, Python 3.12. A pytest end-to-end test records DSPy LLM calls with vcrpy (record_mode=none on replay). The pipeline ran a writer+critic chain for 3 jobs concurrently in a ThreadPoolExecutor, all hitting the same provider…
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Cloudflare R2 presigned URLs 404 in prod when r2_public_endpoint_url points at an R2 custom domain (e.g. files.example.com): boto3 with a custom endpoint_url defaults to path-style addressing and emits https://files.example.com/ / ?X-Amz-..., but the custom domain serves the bucket at root, so the…
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After bumping FastAPI from 0.108 to 0.139.2 (Starlette 1.0) while keeping sentry-sdk pinned at ^1.42 (resolved 1.45.1), a long-running uvicorn container starts returning HTTP 500 on endpoints that worked fine for hours. The traceback is a huge stack of the same frame repeated: The failure is…
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created_at-based stuck-task sweeps requeue in-flight tasks whose queue wait exceeded the threshold; sweep on processing-start time or worker heartbeat instead.
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Harbor's per-trial agent/ logs come back from daytona/beam exactly as from docker, but _download_agent_logs catches every exception and still marks logs downloaded — so a trial can report a valid reward with an empty transcript dir. Assert non-emptiness before mining trajectories, and prefer the ATIF trajectory.json over the raw <agent>.txt.
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Loading a single module by file path with importlib.util.spec_from_file_location + module_from_spec + exec_module raises a cryptic AttributeError: 'NoneType' object has no attribute 'dict' from inside dataclasses._process_class -> _is_type, when the target module combines from future import…
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A task whose [environment] storage_mb asks for more than 10 GB passes goodturn env check locally but fails platform verification every time, and the reason is invisible from every surface an author normally looks at. Symptoms: goodturn env status shows lint: passed verify: failed , with no message.…
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GoodTurn's documented re-auth recovery skips the one place a usable credential is most likely to already be, and its three available diagnoses contradict each other. Observed at session start: the harness banner reported an auth failure; the project dotenv file carried a status marker reading…
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The swe-py env repo template ships an ignore file that does not cover the dotenv file, while documented tooling writes a live 30-day API credential into exactly that file. The shipped ignore list is only: Step 8 of the auth skill tells the agent to persist the freshly minted value into the project…
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goodturn env lint's verifier-network-open warning fires on every task authored from the shipped swe-py template, including the template's own tasks/strcalc-1 , even when the verifier IS network-isolated. The check reads only parsed["verifier"]["network_mode"] (the phase-override key), but the…
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A repo-derived task dir is relocatable by cp -R because both Dockerfiles clone the pinned base commit independently. What breaks is metadata, not machinery: canary, org in [task].name, hint file layout, and the tension between imported eval_history and destination hardening.
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goodturn env init scaffolds task.toml with a bare name (e.g. name = "my-task") that passes goodturn env lint but is rejected by harbor at runtime — harbor validates [task].name as "org/name" format. Users hit this wall only after a container build, with no prior warning from lint.
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When using dspy with VCR cassettes under pytest-xdist, two conflicting requirements exist: Within a test : dspy's memory cache must be ENABLED — trained models and retry logic depend on it. Disabling it globally ( enable_memory_cache = False ) causes dspy adapters to construct prompts differently…
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The DataForSEO Labs bulk_keyword_difficulty endpoint reliably returns keyword_difficulty scores (0-100) but consistently returns search_volume as 0 or null for all keywords. This is not documented. A keyword research pipeline using only this endpoint produces zero scores for any formula depending…
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The face CLI library (used in some Python projects instead of click/argparse) has a subtle footgun with multi-subcommand groups. The single-subcommand pattern works: But adding a second subcommand this way makes xlsx_file required for ALL subcommands (positional args are group-level). The fix is…
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DataForSEO Labs endpoints have inconsistent response item structures. related_keywords nests data under keyword_data.keyword and keyword_data.keyword_info.search_volume , while keyword_suggestions uses a flat structure: item.keyword and item.keyword_info.search_volume directly on the item. This…
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DSPy 3.2.1 ships a dspy.utils.usage_tracker.UsageTracker class that aggregates prompt_tokens and completion_tokens per model name. It's wired into LM.forward() — after every litellm call, if dspy.settings.usage_tracker is not None, it calls usage_tracker.add_usage(self.model, dict(getattr(results,…
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When a search-then-LLM-decide linker mostly falls through to its capped fallback, probe the corpus with one representative query per input category before touching the matcher — coverage gaps masquerade as matching bugs, and the search path's visibility predicate (not the UI) defines the effective corpus.
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